Examining TCP parallelization related methods for various packet losses

The diversity of the networks (wired/wireless) prefers a TCP solution robust across a wide range of networks rather than fine-tuned for a particular one at the cost of another. TCP parallelization uses multiple virtual TCP connections to transfer data for an application process and opens a way to improve TCP performance across a wide range of environments - high bandwidth-delay product (BDP), wireless as well as conventional networks. In particular, it can significantly benefit the emerging high-speed wireless networks. Despite its potential to work well over a wide range of networks, it is not fully understood how TCP parallelization performs when experiencing various packet losses in the heterogeneous environment. This paper examines the current TCP parallelization related methods under various packet losses and shows how to improve the performance of TCP parallelization.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Dietary and nutritional aspects of tooth wear

There is a general perception that the problem of tooth wear is increasing due to elements of the modern diet and due to increased retention of dentition into older age. Tooth wear encompasses erosion, abrasion and attrition of dental tissues – these often co-exist – yet in general, erosion is of more significance to the young and attrition is of more significance to the older population. Diet plays a significant role in the aetiology of tooth wear and likewise advanced tooth wear in older age may impose dietary restrictions with consequences for dietary intake and nutritional status. There is a need to increase the awareness of the disease of tooth wear and the associated nutritional problems. At present, the aetiology of tooth wear is poorly understood – especially with respect to the role of diet. Clearer information on how best to measure and monitor the incidence and prevalence is needed in order to obtain longitudinal data on trends in tooth wear and to monitor the factors that contribute to this condition. These issues will be addressed in the following presentations: 1) What is tooth wear? Aetiology, measurement and monitoring, 2) The role of diet in the aetiology of dental erosion, 3) Groups at increased risk of tooth wear: Eating disorders, ‘dieters' sportsmen and those with impairments, 4) Tooth wear in older adults: nutritional implications. In summary this symposium seeks to: 1) increase awareness of the disease of tooth wear, and its associated nutritional problems 2) increase understanding of the aetiology of tooth wear, especially the dietary role, 3) provide information on how to measure and monitor tooth wear, 4) highlight future research requirements in the area of tooth wear and diet.